Strategic resource planning is an essential tool for many companies and organizations. Strategic resource planning allows companies to acquire the resources that they need in the amounts that they need, when they are needed. These resources can include goods, raw materials, services, manpower, facilities and a wide range of other things.
The value of strategic resource planning depends entirely on its accuracy. Inaccurate forecasting is, in many cases, worse than no forecasting at all. As a result, a great deal of energy has been invested in creating accurate methods for forecasting. Unfortunately, forecasts will always be imperfect. Therefore, the planner will always be faced with the financial risks associated with over- and under-supply. The real business challenge is to effectively manage the risks of planning under uncertainty.
Risk management requires explicit consideration of multiple possible outcomes and their likelihood (or probability) of occurring. In this case, multiple possible outcomes arise because the demand forecast is not clairvoyant. The probability that any particular outcome will occur is related to the uncertainty around the demand forecast. Existing systems do not treat the uncertainty of demand forecasts explicitly. Instead of explicitly quantifying these uncertainties, existing systems merely assume that demand forecasts may be inaccurate. As a result, the degree of uncertainty is never elicited for use in a formal analysis. When the underlying demand data is not represented probabilistically, risk management methods are difficult if not impossible.
Resource planning for resources consumed in the assembly (creation or manufacture) or refinements (from which value is derived) is a particular complex task as demand for resources is actually driven by demand for the refinements. Moreover, while costs are associated with positioning resources, it is ultimately the availability of refinements that provides revenue.
Demands for finished goods often have relationships that can be described as neutral, cannibalistic or synergistic. Goods that have synergistic relations tend to boost each other's sales. This happens when the products tend to be used together, such as a computer system and monitor. Goods that have cannibalistic relations compete for sales. This happens when one good is used in place of the other, such as a computer system and a slightly faster computer system. Unfortunately, existing systems and methods for strategic resource planning do not capture explicitly or use the demand relations among finished goods. As a result, these systems tend to produce sub-optimal results.
Existing systems do not explicitly capture time based resource availability in the form of contractual terms that provide supply flexibility around a specific resource plan. Very often planned quantities of resources for refinement can be canceled (at costs), or additional quantities can be expedited (at costs) as a reaction to real demand.
Existing systems calculate resource demands from refinement demands and may provide a measure of refinement availability from resource availability (given resource allocation rules). However, existing systems assume demand information to be deterministic (single forecast estimate). Existing systems are not able to connect demands for refinements and implied demands for resources, as well as availability of resources and implied availability of refinements.
Finally, existing systems do not have the ability to provide performance measures on cost exposure, revenue, profit and availability risks at both refinement and resource levels that account for the uncertainty and demand dynamics for refinements competing for scarce resources.